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J-SPACE:一个用于模拟癌症进化和测序实验的空间模型的 Julia 包。

J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.

机构信息

Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.

Department of Mathematics and Geosciences, Univ. of Trieste, Trieste, Italy.

出版信息

BMC Bioinformatics. 2022 Jul 8;23(1):269. doi: 10.1186/s12859-022-04779-8.

Abstract

BACKGROUND

The combined effects of biological variability and measurement-related errors on cancer sequencing data remain largely unexplored. However, the spatio-temporal simulation of multi-cellular systems provides a powerful instrument to address this issue. In particular, efficient algorithmic frameworks are needed to overcome the harsh trade-off between scalability and expressivity, so to allow one to simulate both realistic cancer evolution scenarios and the related sequencing experiments, which can then be used to benchmark downstream bioinformatics methods.

RESULT

We introduce a Julia package for SPAtial Cancer Evolution (J-SPACE), which allows one to model and simulate a broad set of experimental scenarios, phenomenological rules and sequencing settings.Specifically, J-SPACE simulates the spatial dynamics of cells as a continuous-time multi-type birth-death stochastic process on a arbitrary graph, employing different rules of interaction and an optimised Gillespie algorithm. The evolutionary dynamics of genomic alterations (single-nucleotide variants and indels) is simulated either under the Infinite Sites Assumption or several different substitution models, including one based on mutational signatures. After mimicking the spatial sampling of tumour cells, J-SPACE returns the related phylogenetic model, and allows one to generate synthetic reads from several Next-Generation Sequencing (NGS) platforms, via the ART read simulator. The results are finally returned in standard FASTA, FASTQ, SAM, ALN and Newick file formats.

CONCLUSION

J-SPACE is designed to efficiently simulate the heterogeneous behaviour of a large number of cancer cells and produces a rich set of outputs. Our framework is useful to investigate the emergent spatial dynamics of cancer subpopulations, as well as to assess the impact of incomplete sampling and of experiment-specific errors. Importantly, the output of J-SPACE is designed to allow the performance assessment of downstream bioinformatics pipelines processing NGS data. J-SPACE is freely available at: https://github.com/BIMIB-DISCo/J-Space.jl .

摘要

背景

生物变异性和测量相关误差对癌症测序数据的综合影响在很大程度上仍未得到探索。然而,多细胞系统的时空模拟为解决这个问题提供了一个强大的工具。特别是,需要有效的算法框架来克服可扩展性和表达性之间的苛刻权衡,以便模拟现实的癌症进化场景和相关的测序实验,然后可以将这些实验用于下游生物信息学方法的基准测试。

结果

我们引入了一个用于 SPAtial Cancer Evolution (J-SPACE) 的 Julia 包,该包允许对广泛的实验场景、现象学规则和测序设置进行建模和模拟。具体来说,J-SPACE 将细胞的空间动力学模拟为任意图上的连续时间多类型生死随机过程,采用不同的相互作用规则和优化的 Gillespie 算法。基因组改变(单核苷酸变体和插入缺失)的进化动力学在无限位点假设下或几种不同的替代模型下进行模拟,包括一种基于突变特征的模型。在模拟肿瘤细胞的空间采样之后,J-SPACE 返回相关的系统发育模型,并允许从几个下一代测序 (NGS) 平台生成合成读取,通过 ART 读取模拟器。结果最终以标准的 FASTA、FASTQ、SAM、ALN 和 Newick 文件格式返回。

结论

J-SPACE 旨在有效地模拟大量癌细胞的异质行为,并产生丰富的输出。我们的框架可用于研究癌症亚群的新兴空间动态,以及评估不完全采样和特定于实验的误差的影响。重要的是,J-SPACE 的输出旨在允许处理 NGS 数据的下游生物信息学管道的性能评估。J-SPACE 可在以下网址免费获得:https://github.com/BIMIB-DISCo/J-Space.jl。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd82/9270769/4bb70008bac3/12859_2022_4779_Fig1_HTML.jpg

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